Suppr超能文献

未满足的社会需求与憩室炎:一种表型分析算法及横断面分析

Unmet social needs and diverticulitis: a phenotyping algorithm and cross-sectional analysis.

作者信息

Ueland Thomas E, Younan Samuel A, Evans Parker T, Sims Jessica, Shroder Megan M, Hawkins Alexander T, Peek Richard, Niu Xinnan, Bastarache Lisa, Robinson Jamie R

机构信息

Vanderbilt University School of Medicine, Nashville, TN 37232, United States.

Division of General Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, United States.

出版信息

J Am Med Inform Assoc. 2025 May 1;32(5):866-875. doi: 10.1093/jamia/ocae238.

Abstract

OBJECTIVE

To validate a phenotyping algorithm for gradations of diverticular disease severity and investigate relationships between unmet social needs and disease severity.

MATERIALS AND METHODS

An algorithm was designed in the All of Us Research Program to identify diverticulosis, mild diverticulitis, and operative or recurrent diverticulitis requiring multiple inpatient admissions. This was validated in an independent institution and applied to a cohort in the All of Us Research Program. Distributions of individual-level social barriers were compared across quintiles of an area-level index through fold enrichment of the barrier in the fifth (most deprived) quintile relative to the first (least deprived) quintile. Social needs of food insecurity, housing instability, and care access were included in logistic regression to assess association with disease severity.

RESULTS

Across disease severity groups, the phenotyping algorithm had positive predictive values ranging from 0.87 to 0.97 and negative predictive values ranging from 0.97 to 0.99. Unmet social needs were variably distributed when comparing the most to the least deprived quintile of the area-level deprivation index (fold enrichment ranging from 0.53 to 15). Relative to a reference of diverticulosis, an unmet social need was associated with greater odds of operative or recurrent inpatient diverticulitis (OR [95% CI] 1.61 [1.19-2.17]).

DISCUSSION

Understanding the landscape of social barriers in disease-specific cohorts may facilitate a targeted approach when addressing these needs in clinical settings.

CONCLUSION

Using a validated phenotyping algorithm for diverticular disease severity, unmet social needs were found to be associated with greater severity of diverticulitis presentation.

摘要

目的

验证一种用于评估憩室病严重程度分级的表型分析算法,并研究未满足的社会需求与疾病严重程度之间的关系。

材料与方法

在“我们所有人研究计划”中设计了一种算法,以识别憩室病、轻度憩室炎以及需要多次住院治疗的手术性或复发性憩室炎。该算法在一家独立机构中得到验证,并应用于“我们所有人研究计划”中的一个队列。通过将第五(最贫困)五分位数相对于第一(最不贫困)五分位数的障碍富集倍数,比较了个体层面社会障碍在区域层面指数五分位数中的分布情况。将粮食不安全、住房不稳定和医疗服务可及性等社会需求纳入逻辑回归,以评估与疾病严重程度的关联。

结果

在不同疾病严重程度组中,表型分析算法的阳性预测值范围为0.87至0.97,阴性预测值范围为0.97至0.99。在比较区域层面贫困指数的最贫困五分位数与最不贫困五分位数时,未满足的社会需求分布各异(富集倍数范围为0.53至15)。相对于憩室病参考组,未满足的社会需求与手术性或复发性住院憩室炎的更高几率相关(比值比[95%置信区间]为1.61[1.19 - 2.17])。

讨论

了解特定疾病队列中的社会障碍情况,可能有助于在临床环境中解决这些需求时采取有针对性的方法。

结论

使用经过验证的憩室病严重程度表型分析算法,发现未满足的社会需求与憩室炎表现的更严重程度相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/08b1/12012367/bf4cec685faf/ocae238f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验